Instructions to use multimolecule/sptransformer with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MultiMolecule
How to use multimolecule/sptransformer with MultiMolecule:
pip install multimolecule
from multimolecule import AutoModel, AutoTokenizer tokenizer = AutoTokenizer.from_pretrained("multimolecule/sptransformer") model = AutoModel.from_pretrained("multimolecule/sptransformer") - Notebooks
- Google Colab
- Kaggle
File size: 1,241 Bytes
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"architectures": [
"SpTransformerModel"
],
"attention_hidden_size": 256,
"batch_norm_eps": 1e-05,
"batch_norm_momentum": 0.1,
"bos_token_id": null,
"bucket_size": 64,
"context": 4000,
"dtype": "float32",
"encoders": [
{
"hidden_size": 128
},
{
"hidden_size": 64
}
],
"eos_token_id": null,
"head": {
"act": null,
"bias": true,
"dropout": 0.0,
"hidden_size": 256,
"layer_norm_eps": 1e-12,
"loss_weight": null,
"num_labels": 15,
"output_name": null,
"problem_type": "regression",
"transform": null,
"transform_act": "gelu",
"type": null
},
"hidden_act": "relu",
"hidden_size": 128,
"id2label": null,
"intermediate_act": "gelu",
"intermediate_size": 1024,
"label2id": null,
"mask_token_id": null,
"max_seq_len": 8192,
"model_type": "sptransformer",
"null_token_id": null,
"num_attention_heads": 8,
"num_hidden_layers": 8,
"num_labels": 15,
"num_local_attention_heads": 2,
"num_splice_labels": 3,
"num_tissues": 15,
"output_contexts": false,
"pad_token_id": 4,
"problem_type": "regression",
"tie_word_embeddings": true,
"transformers_version": "5.7.0",
"unk_token_id": 4,
"vocab_size": 5
}
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